Many factors influence where U.S. tech multinational corporations decide to conduct their global artificial intelligence research and development (R&D). Company AI labs are spread all over the world, especially in North America, Europe and Asia. But in contrast to AI labs, most company AI staff remain concentrated in the United States. Roxanne Heston and Remco Zwetsloot explain where these companies conduct AI R&D, why they select particular locations, and how they establish their presence there. The report is accompanied by a new open-source dataset of more than 60 AI R&D labs run by these companies worldwide.

To help U.S. policymakers address long-held concerns about risks and threats associated with letting Chinese university students or graduates study in the United States, CSET experts examine which forms of collaboration, and with which Chinese universities, pose the greatest risk to U.S. research security.

Half of Silicon Valley’s startups have at least one foreign-born founder, and immigrants are twice as likely as native-born Americans to start new businesses. To understand how immigration shapes AI entrepreneurship in particular in the United States, Huang, Arnold and Zwetsloot analyze the 2019 AI 50, Forbes’s list of the “most promising” U.S.-based AI startups. They find that 66 percent of these startups had at least one immigrant founder. The authors write that policymakers should consider lifting some current immigration restrictions and creating new pathways for entrepreneurs.

In recent years, concern has grown about the risks of Chinese nationals studying science, technology, engineering and mathematics (STEM) subjects at U.S. universities. This data brief estimates the number of Chinese students in the United States in detail, according to their fields of study and degree level. Among its findings: Chinese nationals comprise 16 percent of all graduate STEM students and 2 percent of undergraduate STEM students, lower proportions than were previously suggested in U.S. government reports.

Over the last decade, Moscow has boosted funding of universities and implemented reforms in order to make Russia a global leader in AI. As part of that effort, Russian researchers have expanded their English-language publication output, a key—if imperfect—measure of the country’s innovation and impact. Between 2010 and 2018, the number of English-language publications by Russian scientists in AI-related fields increased six-fold.

The global AI industry is booming, with privately held firms pulling in nearly $40 billion in disclosed investment in 2019 alone. U.S. companies continue to attract the majority of that funding—64 percent of it in 2019—but that lead is not guaranteed. This report analyzes AI investment data from 2015 to 2019 to help better understand trends in the global AI landscape.

Future U.S. competitiveness in artificial intelligence will require a robust AI workforce. This data brief analyzes market demand for AI-related jobs to determine the skills necessary in the field. It concerns jobs considered both “core AI” and “AI-adjacent.”

Technical leadership in the semiconductor industry has been a cornerstone of U.S. military and economic power for decades, but continued competitiveness is not guaranteed. This issue brief exploring the composition of the workforce bolstering U.S. leadership in the semiconductor industry concludes that immigration restrictions are directly at odds with U.S. efforts to secure its supply chains.

Since 2016, China has engaged in a nationwide effort to "merge" AI and neuroscience research as a major part of its next-generation AI development program. This report explores China’s AI-brain program — identifying key players and organizations and recommending the creation of an open source S&T monitoring capability within the U.S. government.

The United States must adopt a new approach to R&D policy to optimize the diversity of the current system, manage the risks of system dispersion and deliver the benefits of R&D to society. This policy brief provides a new framework for understanding the U.S. R&D ecosystem and recommendations for repositioning the role of the federal government in R&D.